An event detection and monitoring system detects the occurrence of a system event and creates a record of the event. Event log files are created by many different programs to record different types of events for later analysis, and can be sorted and ordered by categories such as time, date, event type, and the like. While log files in tabular format do provide a wealth of information about individual events in isolation, they do not readily illuminate patterns or clusters of events that in the aggregate may help to isolate or narrow a problem that may be causing the events being reported.
When an event occurs that is recorded, relevant information about the event is placed into an event log or log chart, often displayed on a computer screen. Typically, an event log or log chart is a text file with one or more lines of text describing each event. Event logs may also include sorting criteria such as time of the event or of the report, name of the event, type of event, person reporting or on the scene, error code, etc. For a reader seeking a broad overview of numerous events in context with one another, reading the text-based event log presents too much detail and obscures relationships between groups of events. Data from the event log is therefore sometimes put into a graphical format, preferably a chart, that displays only some of the data of the event log for many events simultaneously. The event log may be ongoing and updated as events occur, such as safety system monitoring and maintenance at a chemical manufacturing plant, or it may be a compilation of historical events, such as automated in-flight measurements downloaded from an aircraft after landing for analysis.
One usability problem with log tables (data presented in a tabular format) is that the format makes it difficult for a user to explore the tabular data except as individual entries of discrete events. Log tables may contain hundreds or thousands of rows of entries, which can be tedious for the user to quickly explore or navigate in order to find the desired entry or to identify a pattern of events. Conventional sorting and filtering software and controls can assist in culling the volume of data to absorb, but these do not take advantage of data visualization that can facilitate a data mining and exploring mode of interaction. Conventional sorting and filtering controls assume that users know the information they are searching for and would benefit from exploring general patterns of activity that might be more readily apparent by viewing a chart. Data visualization is a higher-level user interaction approach, and another tool for users in determining and analyzing problems. However, as the user drills down to the root of the problem using the chart presentation, the log table might provide the next level of more detailed information for problem determination. Both types of event log format presentations—tabular and chart—provide different benefits. Tight coupling between log tables and log charts provide the user with a more robust tool, facilitating data exploration and providing synergy.
Currently, there are systems capable of converting data that is in tabular format into chart format. See for example Japanese Patent Nos. 2000200302 by Nishemura Hidenori et al. and U.S. Pat. No. 4,760,458 by Watanabe et al. There are also systems capable of graphing stored data. See for example Japanese Patent No. 4243493A to Nakabayashi Kazunori et al.
There are no currently available systems known to the inventors that are capable of tightly coupling events in a log table to a log chart and events from a log chart to a log table, thereby creating two-way connections. This invention provides a two-way connection between data is a tabular format and data in a chart format.